Directed Sonar Sensing for Mobile Robot Navigation

  title={Directed Sonar Sensing for Mobile Robot Navigation},
  author={John J. Leonard and Hugh F. Durrant-Whyte},
List of Figures. List of Tables. List of Abbreviations and Symbols. Preface. 1. Introduction. 2. A Sonar Sensor Model. 3. Model-Based Localization. 4. Map Building. 5. Simultaneous Map Building and Localization. 6. Directed Sensing Strategies. 7. Why Use Sonar? A. Hardware and Software. Bibliography. Index. 
Navigation in realistic environments
An accurate and robust algorithm for Simultaneous Localization and Map Building (SLAM) to enable a mobile robot to build an internal representation (Map) of an unexplored environment while simultaneously using that map to navigate.
Model-based sonar localisation for mobile robots
  • B. Triggs
  • Computer Science
    Robotics Auton. Syst.
  • 1994
Sonar resolution-based environment mapping
A set of range readings from a ring of sonars are correlated to acquire a 2D map of the robot's environment that is continuously enhanced via novel matching and update algorithms as new data are collected while the robot is in motion.
Concurrent localisation and map building for mobile robots using ultrasonic sensors
  • W. Rencken
  • Computer Science
    Proceedings of 1993 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS '93)
  • 1993
This paper presents an approach where the boot-strapping problem of concurrent localization and map building is solved by estimating the respective errors introduced by each of the processes and correcting them accordingly.
Set membership localization of mobile robots via angle measurements
The proposed set membership estimation procedure exploits the structure of the static set estimator, to solve recursively the dynamic localization problem for a mobile robot navigating in an unstructured outdoor environment.
Global Integration of Ultrasonic Sensors Information in Mobile Robot Localization
The proposed algorithm is based upon an extended Kalman filter, which utilizes matches between observed geometric beacons projections and an a priori map of beacon locations, to correct the position and orientation of the vehicle.
Obstacle Avoidance and Path Planning Using a Sparse Array of Sonars
This paper proposes an exploration method for robots equipped with a set of sonar sensors that does not allow for complete coverage of the robot’s close surroundings that minimizes such risks while guiding the robot towards a predefined target location.
Landmark perception planning for mobile robot localization
This paper presents a fuzzy perception planner that takes into account the time cost, the suitability of every landmark detection and the different uncertainties the robot encounters along its path
Constructing maps for mobile robot navigation based on ultrasonic range data
  • Andreas Kurz
  • Computer Science
    IEEE Trans. Syst. Man Cybern. Part B
  • 1996
An approach to generating environmental maps based on ultrasonic range data by means of a learning classifier that can be partitioned into situation areas which are defined as regions wherein a specific situation can be recognized.


Laser-radar based mapping and navigation for an autonomous mobile robot
The environment mapping and navigation components of MOBOT-III are described. MOBOT-III is a laser-radar-based autonomous mobile robot designed to operate in an unknown indoor environment with moving
Combining Sonar and Infrared Sensors for Mobile Robot Navigation
  • A. Flynn
  • Computer Science
    Int. J. Robotics Res.
  • 1988
Sonar and infrared sensors are used here in a complementary fashion, where the advantages of one compensate for the disadvantages of the other, to build a more accurate map.
Mobile Robot Localization Using Sonar
  • M. Drumheller
  • Physics
    IEEE Transactions on Pattern Analysis and Machine Intelligence
  • 1987
A method by which range data from a sonar rangefinder can be used to determine the two-dimensional position and orientation of a mobile robot inside a room, which is extremely tolerant of noise and clutter.
Stereo vision and navigation in buildings for mobile robots
A mobile robot that autonomously functions in a complex and previously unknown indoor environment has been developed that uses stereo vision, odometry, and contact bumpers to instantiate a symbolic world model.
Mobile robot localization by tracking geometric beacons
An algorithm for, model-based localization that relies on the concept of a geometric beacon, a naturally occurring environment feature that can be reliably observed in successive sensor measurements and can be accurately described in terms of a concise geometric parameterization, is developed.
Obstacle avoidance with ultrasonic sensors
The obstacle avoidance strategy used for this robot is described, which depends heavily on the performance of the ultrasonic range finders, these sensors and the effect of their limitations on the obstacle avoidance algorithm are discussed in detail.
Dynamic map building for autonomous mobile robot
Presents an algorithm for autonomous map building and maintenance for a mobile robot that associate a validation measure to represent the belief in the validity of a target, in addition to the usual covariance matrix to represent spatial uncertainty.
A mobile robot: Sensing, planning and locomotion
The architecture of a Stanford's autonomous mobile robot is described including its distributed computing system, locomotion, and sensing, and some of the issues in the representation of a world model are explored.
Prolog-Based World Models For Mobile Robot Navigation
This work describes a method of autonomous programming for mobile robots that uses a Prolog-based world model to represent the feature locations, thereby determining the robot's path through its environment.
Application of multi-target tracking to sonar-based mobile robot navigation
An approach to mobile robot navigation that unifies the problems of obstacle avoidance, position estimation, and map building in a common multi-target tracking framework and an implementation of model-based localization that achieves robust position estimation in a known environment is presented.